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MongoDB is one of the most coveted and admired NoSQL databases for professional development. Its flexibility, scalability and handling of large volumes of data make it the first choice for modern applications.
Aggregation can be understood as aggregation. The Aggregation operation handles data records and returns calculated results. The operations group the values from multiple documents together, and can perform multiple operations on the grouped data to return a single result. In SQL, count (*) and GROUP BY are equivalent to Aggregation in MongoDB.
You have seen the use of MongoDB ObjectId in previous chapters. In this chapter, we will understand the structure of ObjectId.
Replication is the process of synchronizing data from multiple servers. Replication provides redundancy and increased data availability for multiple data copies on many different Database Servers. Replication protects a database from the loss of a particular Server. Replication also allows you to recover data from hardware errors or service disconnections. With additional data copies, you can use it for recovery, reporting, or backup.
Sharding is a process of storing data records across multiple devices and it is a method of MongoDB to meet the requirement for increasing data. When the size of the data increases, a single device cannot be enough to store data.
To create a database Backup in MongoDB, you should use the mongodump command. This command will dump all Server data into dump directory. There are many options available from which you can limit the amount of data or backup created by Remote Server.
When you are preparing a MongoDB Deployment, you should understand how your application is being supported in Production.
Relationship in MongoDB represents how the Documents are related. Relationship can be modeled through the Embeded and Referenced method.
As shown in the Relationship chapter in MongoDB, to deploy a standardized database structure in MongoDB, we use the Referenced Relationship concept, also known as Manual References, in which we manipulate to store the id of the Documents referenced in another Document.
When all fields in the query are part of the index, MongoDB connects query conditions and returns the result by using the same index without looking inside the Document. When indexes are present in RAM, retrieving data from indexes is faster when compared to retrieving data by scanning all documents.
Analyzing queries is a very important aspect to assess the effectiveness of Database and the effectiveness of the designed index. We will explore the two most frequently used queries, $ explain and $ hint.
MongoDB does not support Atomic Transaction over multiple Documents. However, it provides Atomic Operations on a single Document. Therefore, if a Document has hundreds of fields, the update command will either update all those fields or not update any fields, thus maintaining Atomicity at the Document level.
Create an index on the array ie create separate indexes for each of its fields. So in this situation, when we create an index on the array of tags, individual indexes will be created for their values: music, cricket and blogs.
Each index not only occupies part of the memory space but also causes an overhead on each insert, update, and delete operation. So, if you rarely use your Collection for read operations, you should not use the index for it.
In MongoDB Documentation, Map-Reduce is a data processing system that condenses a large amount of data into useful overall results. MongoDB uses mapReduce command for Map-Reduce operation. In general, Map Reduce is used to handle large data sets.
Starting with version 2.4, MongoDB started supporting Text Indexes to search within the string content.
Regular Expression is used frequently in all languages to search for a pattern or a word in any string. MongoDB also provides Regular Expression to match Pattern matching in string by using $ regex operator. MongoDB uses PCRE (Perl Compatible Regular Expression) as the Regular Expression language.
Rockmongo is a MongoDB management tool. Using it, you can manage your Server, Database, Collection, Document, Index, .... It provides a very friendly way for users to read, write and create documents. Rockmongo is quite similar to PHPMyAdmin tool for PHP and MySQL.
MongoDB does not have the auto-increment out-of-the-box feature like SQL Database. By default, it uses a 12-byte ObjectId for the _id field as the Primary key to uniquely identify the Documents. However, there are situations when we want the _id field to have some values that automatically increase beyond ObjectId.
GridFS is the MongoDB Specification for storing and collecting large files such as images, audio, video files, etc. It is a type of file system to store files but its data is stored inside MongoDB collections. .